Clinical feasibility of deep learning-based synthetic CT images from T2-weighted MR images for cervical cancer patients compared to MRCAT

Abstract This work aims to investigate the clinical feasibility of deep learning-based synthetic CT images for cervix cancer, comparing them to MR for calculating attenuation (MRCAT). Patient cohort with 50 pairs of T2-weighted MR and CT images from cervical cancer patients was split into 40 for tra...

ver descrição completa

Detalhes bibliográficos

Principais autores:	Hojin Kim, Sang Kyun Yoo, Jin Sung Kim, Yong Tae Kim, Jai Wo Lee, Changhwan Kim, Chae-Seon Hong, Ho Lee, Min Cheol Han, Dong Wook Kim, Se Young Kim, Tae Min Kim, Woo Hyoung Kim, Jayoung Kong, Yong Bae Kim
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Nature Portfolio 2024-04-01
coleção:	Scientific Reports
Assuntos:	Synthetic CT images MR images Deep learning MRCAT Cervical cancer
Acesso em linha:	https://doi.org/10.1038/s41598-024-59014-6
Tags:	Adicionar Tag Sem tags, seja o primeiro a adicionar uma tag!